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Efficient urban land use is a cornerstone of sustainable city development, yet the drivers of such efficiency are increasingly complex in an era of spatial transformation. As industrial specialization and collaboration deepen, cities are becoming interconnected through complex networks. These “invisible threads” are redefining the dynamics of land use and spatial efficiency. This study examines the influence of intercity industrial networks on urban land use efficiency by constructing urban networks from multi-regional input–output data and evaluating city performance using a super-SBM model. We employed Tobit regression and mediation analysis to identify the mechanisms. Results indicate that both the quantity and quality of urban network connections significantly enhance land use efficiency, with notable differences across city types. The positive effect of industrial network centrality is most pronounced in large cities. In growing cities, both the number and quality of industrial linkages promote efficiency, whereas in shrinking cities, connection quality is more critical than quantity. Mechanism analysis reveals that industrial networks improve land use efficiency primarily by expanding intermediate goods markets and fostering technological innovation.

Optic disc melanocytoma (ODMC) with peripapillary hyperreflective ovoid mass-like structures (PHOMS) is rare. This study reports a case of the characteristics of multimodal imaging and Minimum intensity projection (Min-IP) images. A 25-year-old male patient was referred to our hospital due to the presence of a dark pigmented tumor located in the optic disc area of his left eye. The patient exhibited normal pupillary reactions and had a best corrected visual acuity of 1.0 (decimal) in both eyes. This patient underwent multimodal retinal imaging examination including color fundus photograph (CFP), B-scan ultrasonography, Fundus autofluorescence (FAF), SD-OCT (spectral-domain optical coherence tomography), OCTA (optical coherence tomography angiography), en-face Min-IP image and fluorescein angiography (FA). CFP revealed a slightly elevated mass lesion in the inferior quadrant of the left optic disc, the lesion appeared black to dark brown in color. B-scan ultrasonography of the left eye confirmed the presence of a hyperechoic small dome-shaped lesion. Fundus autofluorescence (FAF) analysis revealed complete hypofluorescence in this area. SD-OCT (spectral-domain optical coherence tomography) and OCTA (optical coherence tomography angiography) with Min-IP were performed over the tumor and its surrounding areas. SD-OCT showed an elevated tumor mass arising from the optic disc with increased reflectivity. PHOMS appeared ovoid in shape on B-scan OCT image. PHOMS appeared peripapillary hyperreflective bright areas on en-face Min-IP image corresponding to PHOMS on B-scan OCT image. The fluorescein angiography (FA) showed the staining of PHOMS. A diagnosis of optic disc melanocytoma with PHOMS was established prompting the patient to be advised for regular follow-up. The optic disc melanocytoma with PHOMS is a rare benign ocular lesion that requires minimal active intervention, but demands a lifetime follow-up. The multimodal imaging and Min-IP images have clinical diagnostic value.

Spontaneous focal hemorrhage of optic disc in peripapillary hyperreflective ovoid mass-like structures (PHOMS) is rare. This study reports the image features of two cases of spontaneous hemorrhage of an optic disc in PHOMS. : A 51-year-old woman complained of visual fatigue for 1 week. Small patchy hemorrhage was observed in the optic disc of the right eye. : A 17-year-old female presented with complaints of experiencing floaters in the left eye for a duration of 1 day. Small patchy hemorrhage was observed in the left optic disc. The patients underwent the color fundus photograph (CFP), fundus autofluorescence (FAF), spectral-domain optical coherence tomography (SD-OCT), optical coherence tomography angiography (OCTA), and Minimum intensity projection (Min-IP) images. : The right eye showed a small patchy hemorrhage of optic disc. PHOMS on SD-OCT of both eyes exhibited an ovoid shape and manifested as peripapillary hyperreflective bright regions on en-face Min-IP image, the active blood flow signal of PHOMS was detected on SD-OCT/OCTA and FAF revealed a hypofluorescent. The optic cup-to-disc (C/D) ratio of both eyes was 0.06, respectively. : Small patchy hemorrhage was observed in the left optic disc and FAF showed hypofluorescence. PHOMS on SD-OCT of the left eye showed an ovoid shape and manifested as peripapillary hyperreflective bright regions on en-face Min-IP image, the active blood flow signal of PHOMS was detected on SD-OCT/OCTA. C/D in the right eye was 0.4. Spontaneous focal hemorrhage of optic disc may occur in PHOMS. The space-occupying effect of PHOMS may lead to compression of surrounding tissues, resulting in the optic disc congestion and a reduced C/D ratio, thereby involving the microvascular system of the optic disc.

Petroleum refineries are one of the main sources of hazardous air pollutants, so the accurate determination of petroleum pollutants is of great significance to maintain ecological balance. In this study, three-dimensional (3D) fluorescence spectroscopy combined with pattern recognition algorithm is adopted to distinguish the composition and content of oil pollutants efficiently and accurately. Three hundred samples of kerosene, diesel, and gasoline mixed solutions with different concentrations are prepared. The principal component analysis is used to extract the optimal feature variables, and the correlation coefficient method is used to obtain eight groups of principal component features in the spectra. The dimension is selected as 8, and the principal component score is calculated, which is used as the input data of the extension neural network. Next, the pattern recognition method is improved, and the designed neural network has functions of both resolution and measurement. The results of neural network pattern recognition are used as the input of the concentration network. The first 270 samples are used as the training samples to train the network model, and the remaining 30 samples are used as test samples, which are applied to the input layer of the trained neural network. The relative fluorescence intensity, relative slope, and comprehensive background parameters are used as the input parameters, and the extension neural network is used for pattern recognition and evaluation of oil pollutants. The experimental results show that the average recognition rate of the improved pattern recognition algorithm for oil pollutants is 98.43%, and the average recovery rate of concentration is 98.67%. Further, the average time for pattern recognition is 1.53 s, while the parallel factor analysis algorithm takes 2.89 s. This suggests that the improved extension neural network is an effective and reliable pattern recognition method for the identification of mixed oil pollutants.

Animal growth and development are regulated by the growth hormone receptor (GHR). To elucidate the transcriptional regulation mechanism of the yak GHR gene, we cloned its proximal promoter region and performed bioinformatic analyses. Deletion constructs were generated to produce fragments of the proximal promoter, and the fragment exhibiting the highest activity was identified using a dual-luciferase reporter assay system. Moreover, the functionality of the transcription factor binding sites was confirmed via site-directed mutagenesis and electrophoretic mobility shift assay (EMSA). Bioinformatics analysis revealed two transcriptional initiation sites were located in the upstream regulation region at positions − 277/ − 327 and − 1734/ − 1784 bp, and CpG islands were located at − 552/ − 654 and − 82/ − 289 bp upstream. We identified the − 160 to + 27 bp region as the minimal core promoter of the yak GHR gene. The transcription factor KLF5, which is involved in muscle growth and development, was predicted to bind the proximal minimum core promoter region of the GHR gene. Using site-directed mutagenesis and EMSA, we demonstrated that KLF5 is a critical transcription regulator of the GHR gene. Our findings establish a theoretical basis for investigating the regulatory mechanisms of GHR gene expression.

The sustainable medical supplier selection (SMSS) is an important issue facing the medical industry in the context of sustainable development, which can be regarded as a typical multi-attribute group decision making (MAGDM) problem. In the MAGDM process, linguistic term set (LTS) is particularly natural and convenient for decision makers (DMs) to express evaluation information. Especially, probabilistic linguistic term set (PLTS) is a very critical and effective tool, which can reflect the importance of different linguistic terms. Due to the different preferences and experience of different DMs, they may use multi-granularity probabilistic linguistic term sets (MGPLTSs) to represent different linguistic information. In this article, in order to study the comparison method of MGPLTSs, a new possibility degree formula is firstly proposed and its properties is proved. Then, in order to build a weight model, a possibility degree-based Best-Worst method (BWM) and a probability degree based-maximizing deviation method are established to calculate the subjective weights and objective weights of attributes, respectively. Where after, a MAGDM method is proposed by combining the ELimination Et Choix Traduisant la REalite (ELECTRE) method with Evaluation based on Distance from Average Solution (EDAS) method in the multi-granularity probabilistic linguistic information environment. Finally, the created MAGDM method is applied to the SMSS, and its effectiveness and advantages compared with other existing methods are verified. First published online 17 January 2022

Artificial intelligence can bring convenience to human life. In the field of sports rehabilitation, the application of artificial intelligence is becoming more and more in-depth. This paper is aimed at studying the prevention and detection of sports rehabilitation in the context of artificial intelligence and proposing a compliance control method for lower limb rehabilitation robots based on artificial neural networks. In this paper, a double closed-loop control system is designed: the outer loop is an adaptive impedance control model based on sEMG feedback, and the purpose is to adjust the predicted desired joint trajectories. In the inner loop, a sliding mode iterative learning controller is designed to suppress periodic disturbance and abnormal jitter and achieve stable tracking of the target trajectory. Finally, the control method is simulated and verified by matlab/simulink, and a statistical experiment is done on the patient’s recovery. The experimental results show that the use of artificial intelligence technology can effectively increase the sensitivity of the control system and improve the recovery rate of patients. Compared with the traditional sports rehabilitation control system, the sensitivity is increased by 22.7%, and the patient recovery rate is increased by 10.4%, which is of great significance in the field of sports rehabilitation.

Oocyte quality determines fertilization success during the reproductive period of fish and is affected by a key intrinsic factor: the level of lipid deposition in the yolk. In this study, lipidomics was used to characterize lipid profiles of adipose tissue, liver, serum and ovary to clarify divergent hepatic lipid allocation to fat depots versus ovary in Sichuan taimen (Hucho bleekeri). The results showed that glycerophospholipids (GPs) constituted the most diverse lipid class across all four tissues, with phosphatidylcholine (PC) being the most abundant in each tissue. Relative to adipose tissue, liver, and serum, the ovary exhibited significant enrichment of PC and phosphatidylethanolamine (PE) and higher accumulation of docosahexaenoic acid (DHA)- and arachidonic acid (ARA)-containing GPs and triacylglycerols (TGs), as well as enrichment in TGs, diacylglycerols (DGs), and cardiolipin (CL), compared to adipose tissue. The expression levels of fads6, elovl2, elovl5, dgat1b, dgat2, pparα, nfyb, and fabp7 were higher in the liver, while lpcat1 was highly expressed specifically in the ovary. The results of this study demonstrate that long-chain polyunsaturated fatty acids (LC-PUFAs) exhibited selective enrichment in the ovary, which facilitates yolk lipid deposition and provides structural and energetic support for oocyte development and early embryonic development. From a lipidomic perspective, this study reveals the regulatory characteristics underlying ovarian yolk deposition in H. bleekeri, providing important evidence for understanding the mechanisms of egg quality formation as well as a theoretical basis for broodstock management, artificial propagation, and the improvement of egg and larval quality.

The development level evaluation of regional rural practical talents needs to comprehensively consider a variety of factors. The general development level of rural practical talents in different regions has little difference, but there are significant differences between different factors. This paper proposes a set of scientific indicators for evaluating rural practical talents, which can be used to understand the development status and level of rural practical talents in various regions and to further provide method support for the development level evaluation of rural practical talents in various regions of China. To avoid the overly subjective drawback of setting index weights in the Analytic Hierarchy Process (AHP), we set the indicator weights via the variation coefficient method and fuse the evaluation information based on an aggregation approach with a hybrid-indicator information power operator, which can lead to a more scientific and effective evaluation of the development level of rural practical talents. Finally, we apply the proposed approach to conducting the applied research on real cases, give relevant analysis and suggestions, and propose the training and introduction policies for the rural practical talents, to promote the development of rural revitalization and construction.

This study investigates methane leakage and diffusion from a buried high-pressure natural gas pipeline (8 MPa, 1000 mm diameter) using CFD simulations with the DES turbulence model. Based on homogeneous and layered soil models, the influences of soil porosity (0.46 to 0.54), particle size (10 μm to 100 μm), and soil stratification on the spatial and temporal characteristics of methane diffusion are systematically explored. The simulation results show that (1) methane diffuses from the leak hole to the surrounding soil in an ellipsoidal pattern, with the fastest diffusion speed along the pipeline’s axial direction. (2) In homogeneous soil, within the range of soil parameter values considered in this study, the absolute changes in risk assessment indices (FDR, GDR) caused by soil particle size were more significant; whereas the relative percentage changes in risk assessment indicators caused by soil porosity were more pronounced. (3) In layered soil, the permeability contrast between adjacent layers creates the permeability discontinuity interface effect. When a fine-grained or low-porosity layer overlies a coarse-grained layer, the upper layer acts as a hydraulic barrier, prolonging FDT from 130 s to 354 s while promoting significant horizontal spread at the interface. Conversely, a coarse-grained or high-porosity upper layer accelerates vertical breakthrough. These findings provide a scientific basis for risk assessment, monitoring site optimization, and emergency response planning, particularly in regions with heterogeneous stratified soils.